A pathway-based approach to identify molecular biomarkers in cancer.

Many examples highlight the power of gene expression profiles, or signatures, to provide an understanding of biological phenotypes. This is best seen in the context of cancer, where expression signatures have tremendous power to identify new cancer subtypes and to predict clinical outcomes. Gene expression profiles have been developed to personalize medicine, accurately predicting disease recurrence and tumor response to therapy. The use of these signatures as surrogate phenotypes allows us to link diverse experimental systems, which dissect the complexity of biological systems, with the in vivo setting in a way that was not previously feasible. Taken together, these new genomic tools provide the opportunity to develop rational strategies for treating the individual cancer patient.

Retraction: A genomic strategy to refine prognosis in early-stage non-small-cell lung cancer. N Engl J Med 2006;355:570-80.

To the Editor: We would like to retract our article, "A Genomic Strategy to Refine Prognosis in Early-Stage Non-Small-Cell Lung Cancer,"(1) which was published in the Journal on August 10, 2006. Using a sample set from a study by the American College of Surgeons Oncology Group (ACOSOG) and a collection of samples from a study by the Cancer and Leukemia Group B (CALGB), we have tried and failed to reproduce results supporting the validation of the lung metagene model described in the article. We deeply regret the effect of this action on the work of other investigators.

The lung cancer exercise training study: a randomized trial of aerobic training, resistance training, or both in postsurgical lung cancer patients: rationale and design.

BACKGROUND: The Lung Cancer Exercise Training Study (LUNGEVITY) is a randomized trial to investigate the efficacy of different types of exercise training on cardiorespiratory fitness (VO2peak), patient-reported outcomes, and the organ components that govern VO2peak in post-operative non-small cell lung cancer (NSCLC) patients. METHODS/DESIGN: Using a single-center, randomized design, 160 subjects (40 patients/study arm) with histologically confirmed stage I-IIIA NSCLC following curative-intent complete surgical resection at Duke University Medical Center (DUMC) will be potentially eligible for this trial. Following baseline assessments, eligible participants will be randomly assigned to one of four conditions: (1) aerobic training alone, (2) resistance training alone, (3) the combination of aerobic and resistance training, or (4) attention-control (progressive stretching). The ultimate goal for all exercise training groups will be 3 supervised exercise sessions per week an intensity above 70% of the individually determined VO2peak for aerobic training and an intensity between 60 and 80% of one-repetition maximum for resistance training, for 30-45 minutes/session. Progressive stretching will be matched to the exercise groups in terms of program length (i.e., 16 weeks), social interaction (participants will receive one-on-one instruction), and duration (30-45 mins/session). The primary study endpoint is VO2peak. Secondary endpoints include: patient-reported outcomes (PROs) (e.g., quality of life, fatigue, depression, etc.) and organ components of the oxygen cascade (i.e., pulmonary function, cardiac function, skeletal muscle function). All endpoints will be assessed at baseline and postintervention (16 weeks). Substudies will include genetic studies regarding individual responses to an exercise stimulus, theoretical determinants of exercise adherence, examination of the psychological mediators of the exercise - PRO relationship, and exercise-induced changes in gene expression. DISCUSSION: VO2peak is becoming increasingly recognized as an outcome of major importance in NSCLC. LUNGEVITY will identify the optimal form of exercise training for NSCLC survivors as well as provide insight into the physiological mechanisms underlying this effect. Overall, this study will contribute to the establishment of clinical exercise therapy rehabilitation guidelines for patients across the entire NSCLC continuum. TRIAL REGISTRATION: NCT00018255.

Refocusing the war on cancer: the critical role of personalized treatment.

Despite very substantial investment and effort over the past 30 years, the overall survival rate of cancer patients has changed little. We propose that without a truly robust mechanism for selecting the right treatment for the right patient at the right time-the central concepts of personalized medicine-we will continue to see only incremental improvements and have little hope for substantial survival gains. We suggest that it is now imperative that future clinical trials be designed with a plan to incorporate biomarker development.

A pathway-based classification of human breast cancer.

The hallmark of human cancer is heterogeneity, reflecting the complexity and variability of the vast array of somatic mutations acquired during oncogenesis. An ability to dissect this heterogeneity, to identify subgroups that represent common mechanisms of disease, will be critical to understanding the complexities of genetic alterations and to provide a framework to develop rational therapeutic strategies. Here, we describe a classification scheme for human breast cancer making use of patterns of pathway activity to build on previous subtype characterizations using intrinsic gene expression signatures, to provide a functional interpretation of the gene expression data that can be linked to therapeutic options. We show that the identified subgroups provide a robust mechanism for classifying independent samples, identifying tumors that share patterns of pathway activity and exhibit similar clinical and biological properties, including distinct patterns of chromosomal alterations that were not evident in the heterogeneous total population of tumors. We propose that this classification scheme provides a basis for understanding the complex mechanisms of oncogenesis that give rise to these tumors and to identify rational opportunities for combination therapies.

Age- and sex-specific genomic profiles in non-small cell lung cancer.

CONTEXT: Gene expression profiling may be useful in examining differences underlying age- and sex-specific outcomes in non-small cell lung cancer (NSCLC). OBJECTIVE: To describe clinically relevant differences in the underlying biology of NSCLC based on patient age and sex. DESIGN, SETTING, AND PATIENTS: Retrospective analysis of 787 patients with predominantly early stage NSCLC performed at Duke University, Durham, North Carolina, from July 2008 to June 2009. Lung tumor samples with corresponding microarray and clinical data were used. All patients were divided into subgroups based on age (< 70 vs > or = 70 years old) or sex. Gene expression signatures representing oncogenic pathway activation and tumor biology/microenvironment status were applied to these samples to obtain patterns of activation/deregulation. MAIN OUTCOME MEASURES: Patterns of oncogenic and molecular signaling pathway activation that are reproducible and correlate with 5-year recurrence-free patient survival. RESULTS: Low- and high-risk patient clusters/cohorts were identified with the longest and shortest 5-year recurrence-free survival, respectively, within the age and sex NSCLC subgroups. These cohorts of NSCLC demonstrate similar patterns of pathway activation. In patients younger than 70 years, high-risk patients, with the shortest recurrence-free survival, demonstrated increased activation of the Src (25% vs 6%; P<.001) and tumor necrosis factor (76% vs 42%; P<.001) pathways compared with low-risk patients. High-risk patients aged 70 years or older demonstrated increased activation of the wound healing (40% vs 24%; P = .02) and invasiveness (64% vs 20%; P<.001) pathways compared with low-risk patients. In women, high-risk patients demonstrated increased activation of the invasiveness (99% vs 2%; P<.001) and STAT3 (72% vs 35%; P<.001) pathways while high-risk men demonstrated increased activation of the STAT3 (87% vs 18%; P<.001), tumor necrosis factor (90% vs 46%; P<.001), EGFR (13% vs 2%; P = .003), and wound healing (50% vs 22%; P<.001) pathways. Multivariate analyses confirmed the independent clinical relevance of the pathway-based subphenotypes in women (hazard ratio [HR], 2.02; 95% confidence interval [CI], 1.34-3.03; P<.001) and patients younger than 70 years (HR, 1.83; 95% CI, 1.24-2.71; P = .003). All observations were reproducible in split sample analyses. CONCLUSIONS: Among a cohort of patients with NSCLC, subgroups defined by oncogenic pathway activation profiles were associated with recurrence-free survival. These findings require validation in independent patient data sets.

Characterizing the clinical relevance of an embryonic stem cell phenotype in lung adenocarcinoma.

PURPOSE: Cancer cells possess traits reminiscent of those ascribed to normal stem cells. It is unclear whether these phenotypic similarities are the result of a common biological phenotype, such as regulatory pathways. EXPERIMENTAL DESIGN: Lung cancer cell lines with corresponding gene expression data and genes associated with an embryonic stem cell identity were used to develop a signature of embryonic stemness (ES) activity specific to lung adenocarcinoma. Biological characteristics were elucidated as a function of cancer biology/oncogenic pathway dysregulation. The ES signature was applied to three independent early-stage (I-IIIa) lung adenocarcinoma data sets with clinically annotated gene expression data. The relationship between the ES phenotype and cisplatin (current standard of care) sensitivity was evaluated. RESULTS: Pathway analysis identified specific regulatory networks [Ras (P = 0.0005), Myc (P = 0.0224), wound healing (P < 0.0001), chromosomal instability (P < 0.0001), and invasiveness (P < 0.0001)] associated with the ES phenotype. The prognostic relevance of the ES signature, as related to patient survival, was characterized in three cohorts [CALGB 9761 (n = 82; P = 0.0001), National Cancer Institute Director's Challenge Consortium (n = 442; P = 0.0002), and Duke (n = 45; P = 0.06)]. The ES signature was not prognostic in prostate, breast, or ovarian adenocarcinomas. Lung tumors (n = 569) and adenocarcinoma cell lines (n = 31) expressing the ES phenotype were more likely to be resistant to cisplatin (P < 0.0001 and P = 0.006, respectively). CONCLUSIONS: Lung adenocarcinomas that share a common gene expression pattern with normal human embryonic stem cells were associated with decreased survival, increased biological complexity, and increased likelihood of resistance to cisplatin. This indicates the aggressiveness of these tumors.

A genomic approach to improve prognosis and predict therapeutic response in chronic lymphocytic leukemia.

PURPOSE: Chronic lymphocytic leukemia (CLL) is a B-cell malignancy characterized by a variable clinical course. Several parameters have prognostic capabilities but are associated with altered response to therapy in only a small subset of patients. EXPERIMENTAL DESIGN: We used gene expression profiling methods to generate predictors of therapy response and prognosis. Genomic signatures that reflect progressive disease and responses to chemotherapy or chemoimmunotherapy were created using cancer cell lines and patient leukemia cell samples. We validated and applied these three signatures to independent clinical data from four cohorts, representing a total of 301 CLL patients. RESULTS: A genomic signature of prognosis created from patient leukemic cell gene expression data coupled with clinical parameters significantly differentiated patients with stable disease from those with progressive disease in the training data set. The progression signature was validated in two independent data sets, showing a capacity to accurately identify patients at risk for progressive disease. In addition, genomic signatures that predict response to chlorambucil or pentostatin, cyclophosphamide, and rituximab were generated and could accurately distinguish responding and nonresponding CLL patients. CONCLUSIONS: Thus, microarray analysis of CLL lymphocytes can be used to refine prognosis and predict response to different therapies. These results have implications for standard and investigational therapeutics in CLL patients.

Age-specific differences in oncogenic pathway dysregulation and anthracycline sensitivity in patients with acute myeloid leukemia.

PURPOSE: To define the biology driving the aggressive nature of acute myeloid leukemia (AML) in elderly patients. PATIENTS AND METHODS: Clinically annotated microarray data from 425 patients with newly diagnosed de novo AML from two publicly available data sets were analyzed after age-specific cohorts (young or= 55 years; n = 144) were prospectively identified. Gene expression analysis was conducted utilizing gene set enrichment analysis, and by applying previously defined and tested signature profiles reflecting dysregulation of oncogenic signaling pathways, altered tumor environment, and signatures of chemotherapy sensitivity. RESULTS: Elderly AML patients as expected had worse overall survival and event-free survival compared with younger patients. Analysis of oncogenic pathways revealed that older patients had higher probability of RAS, Src, and tumor necrosis factor (TNF) pathway activation (all P < .0001). Older patients were also less sensitive to anthracycline compared with younger patients with AML (P < .0001). Hierarchical clustering revealed that younger AML patients in cluster 2 had clinically worse survival, with high RAS, Src, and TNF pathway activation and in turn were less sensitive to anthracycline compared with patients in cluster 1. However, among elderly patients with AML, those in cluster 1 also demonstrated high RAS, Src, and TNF pathway activation but this did not translate into differences in survival or anthracycline sensitivity. CONCLUSION: AML in the elderly represents a distinct biologic entity characterized by unique patterns of deregulated signaling pathway variations that contributes to poor survival and anthracycline resistance. These insights should enable development and adjustments of clinically meaningful treatment strategies in the older patient population.

Genetic heterogeneity of Myc-induced mammary tumors reflecting diverse phenotypes including metastatic potential.

Human cancers result from a complex series of genetic alterations, resulting in heterogeneous disease states. Dissecting this heterogeneity is critical for understanding underlying mechanisms and providing opportunities for therapeutics matching the complexity. Mouse models of cancer have generally been used to reduce this complexity and focus on the role of single genes. Nevertheless, our analysis of tumors arising in the MMTV-Myc model of mammary carcinogenesis reveals substantial heterogeneity, seen in both histological and expression phenotypes. One contribution to this heterogeneity is the substantial frequency of activating Ras mutations. Additionally, we show that these Myc-induced mammary tumors exhibit even greater heterogeneity, revealed by distinct histological subtypes as well as distinct patterns of gene expression, than many other mouse models of tumorigenesis. Two of the major histological subtypes are characterized by differential patterns of cellular signaling pathways, including beta-catenin and Stat3 activities. We also demonstrate that one of the MMTV-Myc mammary tumor subgroups exhibits metastatic capacity and that the signature derived from the subgroup can predict metastatic potential of human breast cancer. Together, these data reveal that a combination of histological and genomic analyses can uncover substantial heterogeneity in mammary tumor formation and therefore highlight aspects of tumor phenotype not evident in the population as a whole.

Polycythemia vera erythroid precursors exhibit increased proliferation and apoptosis resistance associated with abnormal RAS and PI3K pathway activation.

OBJECTIVE: Polycythemia vera (PV) is characterized by erythrocytosis associated with the presence of the activating JAK2(V617F) mutation in a variable proportion of hematopoietic cells. JAK2(V617F) is detected in other myeloproliferative neoplasms, does not appear to be the PV-initiating event, and its specific role in deregulated erythropoiesis in PV is incompletely understood. We investigated the pathogenesis of PV to characterize abnormal proliferation and apoptosis responses and aberrant oncogenic pathway activation in primary PV erythroid precursors. MATERIALS AND METHODS: Peripheral blood CD34(+) cells isolated from PV patients and healthy controls were grown in liquid culture to expand a population of primary erythroblasts for experiments designed to analyze cellular proliferation, apoptosis, JAK2(V617F) mutation status, cytokine-dependent protein phosphorylation and gene expression profiling using Affymetrix microarrays. RESULTS: The survival and proliferation of PV erythroblasts were growth factor-dependent under strict serum-free conditions requiring both erythropoietin (EPO) and stem cell factor. PV erythroblasts exhibited EPO hypersensitivity and enhanced cellular proliferation associated with increased EPO-mediated extracellular signal-regulated kinases 1 and 2 phosphorylation. EPO-induced AKT phosphorylation was observed in PV but not normal erythroblasts, an effect associated with apoptosis resistance in PV erythroblasts. Analysis of gene expression and oncogenic pathway activation signatures revealed increased RAS (p<0.01) and phosphoinositide-3 kinase (p<0.05) pathway activation in PV erythroblasts. CONCLUSION: Deregulated erythropoiesis in PV involves EPO hypersensitivity and apoptosis resistance of erythroid precursor cells associated with abnormally increased activation of RAS-ERK and phosphoinositide-3 kinase-AKT pathways. These data suggest that investigation of the mechanisms of abnormal RAS and phosphoinositide-3 kinase pathway activation in erythroblasts may contribute to our understanding of the molecular pathogenesis of PV.

Utilization of genomic signatures to identify phenotype-specific drugs.

Genetic and genomic studies highlight the substantial complexity and heterogeneity of human cancers and emphasize the general lack of therapeutics that can match this complexity. With the goal of expanding opportunities for drug discovery, we describe an approach that makes use of a phenotype-based screen combined with the use of multiple cancer cell lines. In particular, we have used the NCI-60 cancer cell line panel that includes drug sensitivity measures for over 40,000 compounds assayed on 59 independent cells lines. Targets are cancer-relevant phenotypes represented as gene expression signatures that are used to identify cells within the NCI-60 panel reflecting the signature phenotype and then connect to compounds that are selectively active against those cells. As a proof-of-concept, we show that this strategy effectively identifies compounds with selectivity to the RAS or PI3K pathways. We have then extended this strategy to identify compounds that have activity towards cells exhibiting the basal phenotype of breast cancer, a clinically-important breast cancer characterized as ER-, PR-, and Her2- that lacks viable therapeutic options. One of these compounds, Simvastatin, has previously been shown to inhibit breast cancer cell growth in vitro and importantly, has been associated with a reduction in ER-, PR- breast cancer in a clinical study. We suggest that this approach provides a novel strategy towards identification of therapeutic agents based on clinically relevant phenotypes that can augment the conventional strategies of target-based screens.

An integration of complementary strategies for gene-expression analysis to reveal novel therapeutic opportunities for breast cancer.

INTRODUCTION: Perhaps the major challenge in developing more effective therapeutic strategies for the treatment of breast cancer patients is confronting the heterogeneity of the disease, recognizing that breast cancer is not one disease but multiple disorders with distinct underlying mechanisms. Gene-expression profiling studies have been used to dissect this complexity, and our previous studies identified a series of intrinsic subtypes of breast cancer that define distinct populations of patients with respect to survival. Additional work has also used signatures of oncogenic pathway deregulation to dissect breast cancer heterogeneity as well as to suggest therapeutic opportunities linked to pathway activation. METHODS: We used genomic analyses to identify relations between breast cancer subtypes, pathway deregulation, and drug sensitivity. For these studies, we use three independent breast cancer gene-expression data sets to measure an individual tumor phenotype. Correlation between pathway status and subtype are examined and linked to predictions for response to conventional chemotherapies. RESULTS: We reveal patterns of pathway activation characteristic of each molecular breast cancer subtype, including within the more aggressive subtypes in which novel therapeutic opportunities are critically needed. Whereas some oncogenic pathways have high correlations to breast cancer subtype (RAS, CTNNB1, p53, HER1), others have high variability of activity within a specific subtype (MYC, E2F3, SRC), reflecting biology independent of common clinical factors. Additionally, we combined these analyses with predictions of sensitivity to commonly used cytotoxic chemotherapies to provide additional opportunities for therapeutics specific to the intrinsic subtype that might be better aligned with the characteristics of the individual patient. CONCLUSIONS: Genomic analyses can be used to dissect the heterogeneity of breast cancer. We use an integrated analysis of breast cancer that combines independent methods of genomic analyses to highlight the complexity of signaling pathways underlying different breast cancer phenotypes and to identify optimal therapeutic opportunities.

Gene expression profiles of tumor biology provide a novel approach to prognosis and may guide the selection of therapeutic targets in multiple myeloma.

PURPOSE: Monoclonal gammopathy of undetermined significance (MGUS) and multiple myeloma (MM) comprise heterogeneous disorders with incompletely understood molecular defects and variable clinical features. We performed gene expression profiling (GEP) with microarray data to better dissect the molecular phenotypes, sensitivity to particular chemotherapeutic agents, and prognoses of these diseases. METHODS: Using gene expression and clinical data from 877 patients ranging from normal plasma cells (NPC) to relapsed MM (RMM), we applied gene expression signatures reflecting deregulation of oncogenic pathways and tumor microenvironment to highlight molecular changes that occur as NPCs transition to MM, create a high-risk MGUS gene signature, and subgroup International Staging System (ISS) stages into more prognostically accurate clusters of patients. Lastly, we used gene signatures to predict sensitivity to conventional cytotoxic chemotherapies among identified clusters of patients. RESULTS: Myc upregulation and increasing chromosomal instability (CIN) characterized the evolution from NPC to RMM (P < .0001 for both). Studies of MGUS revealed that some samples shared biologic features with RMM, which comprised the basis for a high-risk MGUS signature. Regarding MM, we subclassified ISS stages into clusters based on shared features of tumor biology. These clusters differentiated themselves based on predictions for prognosis and chemotherapy sensitivity (eg, in ISS stage I, one cluster was characterized by increased CIN, cyclophosphamide resistance, and a poor prognosis). CONCLUSION: GEP provides insight into the molecular defects underlying plasma cell dyscrasias that may explain their clinical heterogeneity. GEP also may also refine current prognostic and therapeutic models for MGUS and MM.